Khaled Waleed Younis Rjoob <br/><br/>
Improving the recognition of heart murmur /  
 تحسين التعرف علي أصوات القلب الغير طبيعية 
Khaled Waleed Younis Rjoob ; Supervised Magd Ahmed Kotb , Hesham N. Elmahdy , Mohammed Ahmed Ahmed Refaey 
 - Cairo :   Khaled Waleed Younis Rjoob ,   2016 
 - 66 Leaves :   charts , facsimiles ;   30cm 
<br/><br/>Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Technology 
<br/><br/> This study built a classication model using hidden markov model (HMM) to recognize heart murmur and chest sounds. Diagnosis of congenital heart and chest defects is challenging, with some being diagnosed during pregnancy while others are diagnosed after birth or later on. Prompt diagnosis allows early intervention and best prognosis. Contemporary diagnosis relies upon the clinical examination, pulse oxime- tery, chest X-ray, electrocardiogram (ECG), echocardiography (ECHO), computed tomography (CT) and cardiac catheterization. These diagnostic modalities reliable upon recording electrical activity, sound waves or upon radiation. Yet, some of congenital heart and pulmonary diseases are still misdiagnosed be- cause of level of physician expertise. In an attempt to improve recognition of heart and chest sounds, we built a classication model for heart murmur and chest sounds recognition using hidden markov model (HMM). This study used mel frequency cepes- tral coecient (MFCC) as a feature and 13 MFCC coecients 
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<br/><br/><label>Subjects--Index Terms: </label>Heart Murmur  Hidden Markov Model (HMM)  Mel Frequency Cepestral Coefficient (MFCC)